Wellcome Open Research

Western blotting has been widely used for decades, yet figure preparation remains unstandardized, error-prone and difficult to audit. Gelato is a free Fiji/ImageJ plugin that streamlines intuitive figure preparation, logs processing coordinates, provides a straightforward audit platform andenables reproduction from raw images. By making these capabilities simple and accessible, Gelato facilitates robust Western blot reporting, reducing a substantial burden on authors and reviewers while strengthening scientific rigor.

Rationale: Plasma proteins are used as biomarkers of inflammation and injury in acute respiratory distress syndrome (ARDS). Whether they vary with body size before ARDS is not well established. Objectives: To determine whether ARDS biomarkers vary with body mass index in adults without acute illness. Methods: We analyzed 8,680 ambulatory adults in the All of Us Research Program with proteomics covering 5,420 protein assays. We grouped 35 proteins associated with ARDS risk or mortality into five compartments by the pathophysiological role assigned in a published systematic review, registered in advance. We modeled body mass index as a restricted cubic spline and reported the difference in each protein between 35 and 25 kg/m2 in standard deviations, adjusted for age, sex, smoking, thirteen chronic conditions and ten genetic principal components. Each estimate was ranked against all 5,420 protein assays. Results: Median age was 50 years, and median body mass index was 27.2 kg/m2. Associations with body mass index across all assays were predominantly positive with a median of 0.065 standard deviations. All four epithelial proteins were lower at higher body mass index, each below at least 92% of assays. Soluble receptor for advanced glycation end products was lower by 0.350 standard deviations and surfactant protein A2, surfactant protein D and club cell secretory protein 16 were lower by 0.081 to 0.084 standard deviations. Interleukin-6 and E-selectin were 0.534 and 0.465 standard deviations higher, above 99% of assays. Differences across body mass index extended to lung enriched proteins outside the prespecified panel. Compartments accounted for 49% of the variance in the 35 protein estimates, against 10% under random reassignment (P < 0.001). At fixed body mass index, type 2 diabetes, hypertension and dyslipidemia showed smaller differences in ARDS biomarkers and were not associated with lower epithelial proteins. Conclusions: Plasma proteins used as biomarkers of inflammation and injury in ARDS vary with body size even in the absence of acute illness. Differences during ARDS may not be attributable to injury alone and may be misinterpreted in patients with obesity due to antecedent variation.

Background: Sexually transmitted infections (STIs) and vaginal dysbiosis during pregnancy are associated with adverse pregnancy outcomes. Mycoplasma genitalium is the most recent STI implicated but evidence remains limited. The objectives of this study were to investigate 1) the association between M. genitalium infection during pregnancy and gestational age at delivery, preterm birth, miscarriage or stillbirth, and low birth weight and 2) the interaction with vaginal dysbiosis. Methods: We conducted a prospective cohort study in East London, South Africa. We enrolled pregnant women at gestational age <27 weeks, confirmed by ultrasound. We tested vaginal samples using nucleic acid amplification tests for M. genitalium, Chlamydia trachomatis, Neisseria gonorrhoeae, Trichomonas vaginalis, other genital mycoplasmas and Candida spp. We defined vaginal dysbiosis using Gram-stain criteria as a Nugent score 4-10. We used quantile regression to compare the outcome in women with and without M. genitalium across the gestational age distribution, adjusting for prespecified sociodemographic and clinical characteristics and co-occurring organisms. Results: From April 1, 2021 to August 29, 2023, we enrolled 603 women, followed up 584 and obtained pregnancy outcomes for 560 (93%). Median age was 28 years (interquartile range, IQR 24, 33) and 27% of women were living with HIV. M. genitalium was detected in 44/584 (8%, 95% CI 6, 10%) and vaginal dysbiosis in 375/584 (64%) of women. Median gestational age at delivery was 39 weeks +0 days (IQR 37+4, 40+1) in women with and 39 weeks +0 days (37+4, 40+0) in those without M. genitalium. In multivariable models, associations were not observed for any adverse birth outcomes. There was no interaction between M. genitalium and vaginal dysbiosis. Discussion: M. genitalium in pregnancy was not associated with earlier gestational age at delivery or with other adverse birth outcomes. These findings do not support routine testing and treatment for M. genitalium in pregnancy.

Background Despite numerous randomized controlled trials (RCTs) and systematic reviews (SRs), current sepsis guidelines continue to issue only weak recommendations for corticosteroids. We examined the clinical scope, underlying study pools, and mortality conclusions of SRs evaluating corticosteroids for sepsis. Methods We conducted a meta-research study of SRs on corticosteroids in sepsis (2015 to 2025), extracting SR characteristics, mortality results, and included RCTs. Study-pool overlap was assessed using an SRxRCT inclusion matrix, Jaccard similarity (J), and hierarchical clustering. SRs and RCTs were classified according to standardized Population, Intervention, Comparison, Outcome (PICO) profiles. We explored discordance in short-term mortality conclusions among clinically comparable SRs and potential associations with study-pool composition, target populations, and methodological characteristics. Results Forty-two SRs including 121 unique RCTs were identified. More than half of pairwise SR comparisons shared no RCTs, and only three pairs showed high overlap (J>0.8). SRs addressing similar intervention and target population profiles frequently relied on different study pools. Among 38 SRs with short-term mortality meta-analyses, 15 (39%) reported benefit and 23 (61%) no evidence of effect. Discordance occurred exclusively among SRs evaluating broad, non-specific corticosteroid strategies; conclusions were consistent for hydrocortisone plus fludrocortisone (benefit) and hydrocortisone, ascorbic acid, and thiamine (no evidence of effect). SRs including sepsis +/- shock populations more frequently reported benefit than those restricted to septic shock (62% vs 22%), although estimates were imprecise. No single methodological or clinical factor consistently explained discordance. Conclusions SRs addressing apparently similar clinical questions frequently synthesized different underlying evidence bases and reported discordant conclusions. Guideline developers should therefore consider not only methodological quality and reported PICO, but also whether the RCTs included in an SR adequately represent the intended clinical question. Clinically coherent evidence syntheses may improve the interpretability of pooled treatment effects and support more targeted corticosteroid therapy in sepsis.

Background FluSurvey is a participatory surveillance system, through which participants report weekly respiratory symptoms, healthcare use and social contacts. To support rapid public health assessment we developed a respiratory self-swabbing feature. We aimed to assess the feasibility of self-swabbing among symptomatic FluSurvey participants. Methods FluSurvey self-swabbing was deployed in England between January-March 2026. Adults reporting recent Acute Respiratory Infection symptoms were eligible for a self-swabbing Covid-19, RSV and Influenza PCR test which was returned to the laboratory by post. Participants were sent optional feedback surveys. We described swabbing interest, timeliness and participant demographics. We evaluated participant feedback to improve the process. Results There were 234 eligible illnesses during the study period; 45.7% (107/234) requested test kits and 93.5%(100/107) test kits were returned. Of these, 97.0%(97/100) had valid results; median participant age was 61.74 years (IQR:47.4-67.4), 68.4% were female and 90.0% were of white ethnicity. All nine regions in England were represented. Timeliness was high; the median time from symptom onset to specimen date was 4.0 days (IQR:3.0-5.0). Of participants completing feedback surveys, 96.7%(59/61) would consider participating in self-swabbing again. Conclusions We developed a tool to test individuals, often not presenting to healthcare, for respiratory viruses using an established community-based surveillance system. This tool can be rapidly deployed and adapted to public health need, to assess community-based emerging respiratory or pandemic infections. The high return rate and positive feedback suggest continued engagement of the cohort in respiratory virus swabbing.

Objectives To characterise COVID-19 inpatients with and without bacterial/fungal preceding, co- and secondary infections, and describe the distribution of organisms associated with COVID-19 and antibiotic use. Methods We linked ISARIC/WHO CCP-UK data from hospitals in England (admissions 01/01/2020-18/10/2021) with UK Health Security Agency infections datasets of COVID-19, and bacterial- and fungal-positive specimens using a multi-step hierarchical algorithm. We retained those aged >18 years and categorised COVID-19-associated infection as preceding (2-28 days prior to SARS-CoV-2 PCR positive date), co-infection ({+/-}1 day) or secondary (2-28 days after). Results During the study period, there were 173,947 hospitalised episodes of COVID-19; 5.8% (n=10,017) with a bacterial or fungal preceding, co- or secondary infection. Preceding and co-infections were rare (preceding: 0.7%; co-infection: 1.5%) while secondary infections were more common (3.5%). Escherichia coli (29.6%) and Staphylococcus aureus (15.2%) were the most identified organisms in blood specimens, while S. aureus (22.9%) and Pseudomonas aeruginosa (20.4%) were most common in lower respiratory tract specimens. The 28-day case fatality rate (CFR) remained static (36%) in those with secondary infection, whereas it decreased between early 2020 and mid-2021 in the other infection groups (37% to 27%). Of those with no positive microbiology, 72.8% received antibiotics, though this decreased between January-June 2020 (77.6%) and April-October 2021 (62.6%). Conclusion Bacterial and fungal infections complicated approximately 1-in-17 hospitalised episodes of COVID-19, with CFR of >25%. Antibiotic prescribing was common in those without firm evidence of bacterial infection. We recommend adhering to NICE guidance which discourages empirical antibiotic use for hospitalised COVID-19 patients.

Abstract Background. Enteric hyperoxaluria (EH) causes calcium oxalate kidney stones, oxalate nephropathy, and chronic kidney disease (CKD), and can progress to end-stage kidney disease. It occurs in Crohn's disease (CD), cystic fibrosis (CF), chronic pancreatitis, celiac disease, short bowel syndrome, and after bariatric surgery. Its prevalence in these populations has not been synthesized. Methods. PROSPERO CRD420261364424. PubMed and Embase were searched to 24 August 2026 for studies reporting 24-hour urinary oxalate. Prevalence was pooled using the Freeman-Tukey double arcsine transformation with a DerSimonian-Laird random-effects model; unweighted crude prevalence is also reported. Because heterogeneity was high, the narrative synthesis stratified by testing condition is the primary result. Prespecified subgroups addressed oxalate load before collection, diagnostic threshold, ileal resection, age, and urine collection format. Results. Forty-seven studies were included. In CD (17 studies, 471 patients; 204 with EH), crude prevalence was 43.3% and pooled prevalence 49.3% (95% CI 38.9-59.8; I^2 = 95.3%). With an oxalate load, prevalence was 64.7% (pooled 74.0%, 55.9-88.6) versus 38.6% without (pooled 39.1%, 28.7-50.0). Among CD patients, EH was more frequent with ileal resection (48.8% vs 31.7%; OR 1.62, 0.91-2.89) and with steatorrhea (62.5% vs 29.3%; OR 9.88, 3.81-25.61). In CF (7 studies, 348 patients; 179 with EH), pooled prevalence was 49.8% (40.5-59.1; I^2 = 91.9%). After bariatric surgery (15 studies, 849 patients; 474 with EH), pooled prevalence was 54.7% (45.4-63.9; I^2 = 96.7%). Conclusions. Roughly half of these patients have EH, but the proportion depends heavily on whether an oxalate load precedes urine collection (39% unprovoked vs 65%-74% provoked); because most studies do not state this condition, published prevalence estimates are not directly comparable. Ileal resection and steatorrhea identify those who should be screened.

Healthcare workers face substantial occupational demands and exposure to respiratory infections during winter, but evidence that probiotics improve their health and wellbeing remains limited. This exploratory, double-blind, randomised, placebo-controlled trial assessed whether daily Lab4 supplementation affected upper respiratory tract infection (URTI) frequency and supported wellbeing in 104 healthcare workers. Daily diaries recorded symptoms defining URTI episodes, general-practitioner visits, illness-related work absence and antibiotic use. Wellbeing was assessed at baseline and weeks 8 and 16, and faecal microbiota were assessed using 16S rRNA gene sequencing. Participants receiving Lab4 reported better wellbeing than those receiving placebo. For probiotic versus placebo, the risk ratio (RR) for URTI occurrence was 0.60 (95% confidence interval [CI]: 0.30-1.20; p=0.1477), the incidence rate ratio (IRR) for episodes was 0.58 (95% CI: 0.27-1.23; p=0.1581), and the mean ratio for episode duration was 0.98 (95% CI: 0.72-1.32; p=0.8776). For general-practitioner visits, the RR for at least one visit was 0.48 (95% CI: 0.21-1.07; p=0.0737) and the IRR was 0.44 (95% CI: 0.18-1.06; p=0.0677). For illness-related work absence, the RR for at least one day absent was 0.75 (95% CI: 0.18-3.22; p=0.6991) and the IRR for absence days was 0.74 (95% CI: 0.16-3.32; p=0.6914). For antibiotic use, the RR for any use was 0.48 (95% CI: 0.20-1.18; p=0.1111) and the IRR for antibiotic-use days was 0.42 (95% CI: 0.16-1.12; p=0.0820). No significant between-group differences in gut microbiota were detected in the subset providing faecal samples. Illness-related estimates generally favoured Lab4, although between-group differences were not statistically significant. These exploratory findings support evaluation in a larger, prospectively powered trial.

Objective Sepsis is a heterogeneous syndrome characterized by substantial variation in infection source, organ dysfunction, and clinical outcomes, and a disproportionate burden in Africa. We aimed to derive and externally validate clinical subphenotypes among adults hospitalized with sepsis in Africa. Design We used latent class analysis with infection source and organ dysfunction as model inputs. We labeled classes post hoc according to their predominant clinical features. We evaluated associations between subphenotypes and 30-day mortality using multivariable logistic regression. Setting Hospitals in Uganda, Rwanda, Liberia, Tanzania, and Malawi. Patients We pooled data from three prospective cohorts of adults hospitalized with sepsis in Uganda, Rwanda, and Liberia for model derivation and independent cohorts from Tanzania and Malawi for external validation. Interventions None. Measurements and Main Results The derivation dataset included 467 adults with sepsis, of whom 128 (27.4%) died within 30 days of admission. Latent class analysis identified four subphenotypes: Class 1 (heterogeneous; n=227; 30.8% mortality), Class 2 (abdominal; n=141; 31.9%), Class 3 (pulmonary; n=68; 16.2%), and Class 4 (soft tissue; n=31; 6.5%). Mortality differed significantly across the four classes (p=0.003). Compared with Class 1, Classes 3 (aOR 0.22, 95% CI 0.10-0.47) and 4 (aOR 0.14, 95% CI 0.02-0.52) had lower odds of 30-day mortality. External validation in 316 adults demonstrated high classification certainty (entropy=0.78; mean maximum posterior probabilities, 0.89-0.92), with similar mortality patterns across corresponding subphenotypes. Conclusions Latent class analysis identified reproducible clinical sepsis subphenotypes defined by infection source and organ dysfunction with distinct mortality risks. These externally validated subphenotypes may improve risk stratification and inform subphenotype-based clinical trials and treatment strategies in Africa.

Objective Although numerous clinical prediction models (CPMs) have been developed to identify pregnancies at risk of serious adverse outcomes, most lack robust external validation, which restricts their reliability in clinical practice. This study aims to systematically review and externally validate existing clinical prediction models for Gestational Diabetes Mellitus (GDM), Pre-eclampsia (PE), Stillbirth, and Small-for-Gestational-Age (SGA) focusing on models for use in pre-conception or early pregnancy. The models were evaluated using a large, representative primary care cohort to assess their performance within a UK population. Method and Analysis A two-stage systematic review identified CPMs for GDM, PE, Stillbirth, and SGA. Eligible models used routinely collected maternal characteristics, fully reported the model equation, and included predictors commonly measured during the preconception or early pregnancy period. Validation was performed using the UK Clinical Practice Research Datalink (CPRD Aurum), including over 1.58 million pregnancies for women aged 14 - 49 between 2000 to 2020. Model performance was assessed through discrimination (C-statistic), calibration-in-the-large (CITL), calibration slope and calibration plot, with pooled estimates across 20 imputations. Results Of 30 studies included, 48 models were identified, comprising 47 binary outcome models and one continuous outcome model, and 23 models used UK cohorts. Models were developed in cohorts comprising 101 to 113,415 participants (median N=5,013). Whilst 29 models have been externally validated, only three have been validated in cohorts including UK population satisfying the requisite sample size. Across all outcomes, most models demonstrated limited generalisability in the UK population. The C-statistic for GDM ranged from 0.29 to 0.77, for PE from 0.42 to 0.71, whilst models for stillbirth and SGA showed weaker discrimination from 0.54 to 0.56 and 0.58 to 0.62, respectively. Models across all outcomes exhibited substantial miscalibration, with calibration-in-the-large ranging from -5.66 to 1.35, and calibration slope from -0.65 to 17.61. Conclusion Existing CPMs for pre-conception and early prediction of adverse pregnancy outcomes showed poor discrimination and frequent miscalibration in a large UK cohort. Whilst some models for SGA had excellent performance, most existing models for GDM, PE, and stillbirth demonstrated suboptimal generalisability, likely a result of differences in population characteristics and outcome prevalence. Therefore, most CPMs evaluated are not suitable for direct implementation in UK clinical practice and require further calibration, updating, even re-development using large, representative data before achieving clinical utility.

Creating high-resolution maps of disease risk is important for many climatically-driven diseases including vector-borne, zoonotic and non-communicable diseases. However, disease counts are commonly only available aggregated to an administrative level such as the county, department or province. Using disease mapping to make high-resolution risk maps from these data can be challenging, even though high-resolution data on temperature and other environmental variables are available. Disaggregation regression is a new multiscale modelling framework that has been used in mapping global malaria incidence and dengue incidence, amongst others. We present Disagapp (https://github.com/simon-smart88/disagapp; https://disagapp.le.ac.uk/) a web app for disease mapping with administrative-level data. The app was designed to be user-friendly, with a point and click interface and with modelling guidance integrated at each step of the analysis. It can be accessed online or run locally by installing the R package and calling one function. Environmental and economic covariates (temperature, precipitation, distance to water, land use, population density, accessibility and night lights) are seamlessly retrieved from various sources, collated and harmonised and used to fit disaggregation regression models using the disaggregation R package. This modelling framework is a principled way to create high-resolution predictions of disease risk. Analyses conducted in the app can be reproduced outside of the app by generating an R markdown document, allowing the user to share, preserve, extend or learn from their analysis. By making the techniques available in the disaggregation package available online and making it simple and easy to access covariates, we remove barriers for non- or novice R users or analysts who work in institutions with restrictive installation permissions to access these innovations. Therefore, this new app makes this important modelling framework much more available to the global modelling community.

Influenza surveillance has typically been carried out using influenza-like illness (ILI) rates and proportions of laboratory tests positive for influenza as metrics to monitor, with sample sizes for the number of tests to carry out based on the precision of the resulting estimate of proportions positive. The transition out of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic period has encouraged the establishment of integrated surveillance of respiratory pathogens, in the context of multiple surveillance objectives, as set out by WHO in its revised integrated surveillance guidance and Mosaic Respiratory Surveillance Framework. These objectives include outbreak detection, situational awareness and intensity evaluation, among others. We illustrate how to design respiratory surveillance in primary care, by considering multiple surveillance objectives for different metrics of different types of respiratory pathogen circulation seasons in England, the USA and Hong Kong. We focus on a proxy of influenza activity as a metric to compare between these countries/regions. Taking advantage of England's integrated sentinel primary care surveillance system, we propose further metrics to monitor: a proxy of respiratory activity, novelly defined as the product of an acute respiratory infection (ARI) consultation rate and the proportion of tests positive for \emph{at least one pathogen}; pathogen-specific ARI-based activity proxies for more detailed monitoring of influenza and SARS-CoV-2; and integrated monitoring of proportions positive for all pathogens tested. We use a simulation approach to determine sample sizes by optimising either the probability of, or time to, detection of different events in monitored metrics, according to the different surveillance objectives. We find that sample sizes to maximise detection probabilities or minimise detection times vary by metric, objective, event and country/region. At a national level, the current sample sizes used are sufficient to detect most events in most weeks for both the USA and Hong Kong, but for England the numbers of swabs taken for ILI consultations may not be sufficient in all weeks, particularly at the start of the season when outbreak detection is important. However, broadening the criteria for swabbing to acute respiratory symptoms does allow for sufficient sample sizes.

Aims To develop a 'core' dataset of diabetes related variables to support reproducible research using UK routinely collected health data. Methods A workshop was conducted bringing together diabetes healthcare professionals, researchers, and patient and public representatives to discuss and prioritise variables for inclusion in the Diabetes Core Dataset. Core variables were those considered to be highest priority for diabetes research and available at high quality in NHS data routinely used for research (primary care [GP] and Hospital Episode Statistics [HES] data). Candidate variables for inclusion in the Diabetes Core Dataset were from a review of existing core datasets and expert opinion. Participants scored variables anonymously based on priority for diabetes research. Results 25 variables from existing diabetes core datasets and 87 other candidate variables were considered for inclusion in the Diabetes Core Dataset. All 25 of those from existing diabetes core datasets and 5 of the 87 candidate variables met the core requirements for inclusion. In addition, 7 variables were identified as high priority but not included in the core dataset as they are not currently available in GP/HES data; these were labelled as 'future high priority' variables for diabetes research. Conclusions A new diabetes core dataset for UK EHR research has been developed using a consensus-based process. The core dataset is openly available and can be flexibly applied in UK EHR (https://healthdatagateway.org/en/tool/426), including in new NHS Research Secure Data Environment platforms, to enhance reproducible research to improve the clinical care of people with diabetes and associated conditions.

Open research practices are increasingly promoted to improve research transparency, reproducibility, accessibility, and societal impact. Despite growing support from research funders, institutions, and policy initiatives, adoption remains uneven across disciplines and research communities. This study examined perceived risks and barriers associated with 14 FORRT Guideline areas using qualitative responses from the UK Reproducibility Network Open and Transparent Research Practices Survey (N = 2,567), conducted across 15 UK higher education institutions. Free-text responses describing risks and barriers were analysed using inductive thematic analysis. A total of 3,951 relevant comments generated 3,433 coded references to barriers and risks. Three interconnected clusters emerged. Individual concerns included lack of motivation, fear of losing intellectual credit, and concerns about exposing mistakes and criticism. Systemic and institutional barriers included lack of time and resources, inadequate infrastructure, insufficient training and support, lack of incentives and recognition, unclear guidance, disciplinary and methodological challenges, and tensions between open practices and intellectual property requirements. Ethical and quality-related concerns included risks to participant confidentiality and privacy, challenges associated with sensitive data, concerns about inappropriate application of open research practices across different research traditions, perceived impacts on research quality and innovation, and potential effects on public trust in research. Lack of time and resources was the most frequently reported barrier. Across responses, barriers were commonly described as interdependent, with shortcomings in funding, infrastructure, institutional support, incentives, and training reinforcing one another. Respondents largely supported the principles underpinning open research but highlighted substantial practical, professional, and ethical challenges to implementation. These findings suggest that increasing open research adoption requires more than policy mandates or awareness-raising activities. Sustainable uptake will depend on aligned incentives, adequate infrastructure and support, recognition of methodological diversity, and approaches that enable openness to be implemented responsibly across different research contexts.

Introduction Aspiration events in hospitalized adults are common and linked to substantial morbidity, mortality, and healthcare burden. While antiemetics have been studied for aspiration prevention in specific settings, evidence for their broader preventive use in hospitalized adults is limited. We conducted a systematic review and meta-analysis to evaluate the effect of prophylactic scheduled antiemetics on aspiration events in adult inpatients. Methods: Ovid MEDLINE, Ovid Embase, CINAHL, and Cochrane Library (via Wiley) were searched in May 2025. We included randomized controlled trials (RCTs) and observational studies assessing prophylactic scheduled antiemetic use in hospitalized adults, with aspiration events as the primary outcome. Secondary outcomes were aspiration pneumonia, hospital length of stay, increased oxygen requirement, ICU admission, and mortality. Two investigators screened and independently extracted data in duplicate using standardized data collection forms. Extracted information included study characteristics, patient demographics and clinical characteristics, interventions, and outcomes. Results: Three RCTs met inclusion criteria (n = 515 patients; 237 antiemetic, 278 placebo). Pooled analysis of two RCTs demonstrated an 88% relative risk [RR] reduction of aspiration events; (2.8% [3/106] prophylactic antiemetic vs 27.9% [29/104] placebo; RR = 0.12, 95% confidence intervals [CI]: 0.02-0.73, p <0.0001, low certainty) in the antiemetic group. Pneumonia rates were also lower in the antiemetic group although they did not reach statistical significance (16.5% vs 32.4%; RR 0.44, 95% CI 0.15-1.28, P = 0.13, low certainty). ICU admission rates were lower in the antiemetic group (2.6% [2/76]) vs. placebo (23% [17/74]); RR = 0.11, 95% CI: 0.03-0.48, p=0.003, very low certainty). Mortality was similar between groups (35.0% vs 38.1%; RR 1.02, 95% CI: 0.84-1.24, P = 0.85, low certainty). No adverse events were reported among all studies. Conclusion: Prophylactic scheduled antiemetics were associated with a significant reduction in aspiration and ICU admission. There was a non-significant but favorable trend towards reduction of pneumonia among hospitalized adults. Larger, high-quality trials are needed to clarify their role in aspiration prevention.

Background Severe COVID-19 is associated with immune dysregulation, microbiome disruption, and increased vulnerability to secondary infections. However, the longer-term risk of acute gastroenteritis (AGE) following COVID-19 remains poorly studied. We compared AGE incidence among community-managed and hospitalised COVID-19 patients with test-negative controls and hospitalised sepsis patients. Methods We conducted a retrospective cohort study using electronic healthcare data. Patients with a recorded SARS-CoV-2 PCR test between 01 March 2020 and 01 March 2022 were allocated to test-negative, community COVID-19, or hospitalised COVID-19 cohorts. A hospitalised sepsis cohort was assembled for an age-, sex- and time-matched analysis. AGE incidence rates were calculated for the two years before enrolment and during follow-up. Negative binomial regression and conditional Poisson models estimated incidence rate ratios (IRRs) adjusting for demographic and clinical covariates. Results Among 788 103 patients, AGE incidence in the pre-pandemic period was higher among individuals later hospitalised with COVID-19 or sepsis compared with community cases. During follow-up, AGE incidence was slightly lower in community COVID-19 cases than test-negative controls (adjusted IRR 0.88 [95% CI 0.85-0.92]), but substantially higher among hospitalised COVID-19 patients (IRR 5.80 [95% CI: 5.38-6.25]). Matched analyses confirmed increased AGE rates compared with community controls (IRR 4.63 [95% CI: 4.15-5.17]) and hospitalised sepsis controls (IRR 1.41 [95% CI 1.21-1.64]). Conclusions COVID-19 hospitalisation is associated with a marked increase in AGE risk after discharge, exceeding that associated with sepsis hospitalisation. By contrast, lower AGE rates in community COVID-19 cases likely reflect baseline differences rather than protective effects of infection. Overall, these findings demonstrate heightened post discharge vulnerability to gastrointestinal illness after COVID 19 hospitalisation and support the need for improved follow up and surveillance strategies.

Nucleic acid extraction remains the principal infrastructure barrier to molecular influenza testing outside centralised laboratories, since bead-based purification is normally tied to mains-powered extractors and trained operators. We evaluated SmartLid, a centrifugation-free format in which a removable magnetic key shuttles paramagnetic beads through pre-aliquoted lysis/binding, wash, and elution buffers without pipetting or powered instrumentation, against an automated magnetic-bead extractor (Nextractor NX-48S) on 311 nasopharyngeal specimens from the 2024-2025 influenza season at a National Influenza Centre. Paired eluates were amplified under identical monoplex RT-qPCR conditions for influenza A(H1N1)pdm09, A(H3), and B/Victoria. Both methods gave 100% specificity (47/47 negatives; no false positives). Subtyping succeeded in 263/264 reference-positive specimens after SmartLid extraction versus 241/264 after automated extraction (99.62% versus 91.29%; difference 8.33 percentage points; discordant pairs 23 versus 1; McNemar P < 0.001). Across 240 complete pairs, cycle threshold (Ct) values were lower after SmartLid extraction (median paired difference -2.78 cycles; estimated location shift -2.60 cycles, 95% CI -2.82 to -2.37; P < 0.001) with rank-ordering of specimens conserved between methods (Spearman rho = 0.84). The advantage was preserved across all three subtypes and in both fresh and frozen specimens (adjusted P < 0.001). Specimens recovered only after SmartLid extraction had higher Ct values than dual-detected specimens (median 34.37 versus 28.54; P < 0.001), locating the gain near the assay detection limit. An instrument-free manual format can therefore exceed the extraction efficiency of an automated reference workflow, extending quality-assured influenza subtyping beyond centralised laboratories.

ObjectivesRespiratory Syncytial Virus (RSV) vaccine policies have varied globally since their approval in 2023. In the UK, policy has adapted in line with National evidence generation such that from Autumn 2026 at-risk persons [&ge;]65 years old will become eligible for vaccination. Immunosuppressed persons <65 years will still not be offered protection. The objective of this study is to investigate the relative burden of RSV infection by age and immunosuppressed status (IC). DesignRetrospective observational cohort study using routine healthcare data from North West London Integrated Care System. ParticipantsPatients with a confirmed diagnosis of a respiratory viral infection (RSV, Influenza A and B, SARS-CoV2) between October 2021 and July 2025. Main outcomes measuresPrevalence and severity of RSV infection in immunosuppressed persons <65 years old, and to provide a comparative analysis with Influenza and SARS-CoV2 in a sub-cohort tested using a 4-in-1 combined rapid PCR test. ResultsDuring the study period, 1226 patients were diagnosed with RSV of whom 596 (48.6%) were <65 years old. In 1091 patients with clinical data, 341 (31.3%) were IC. Fifty (9.9%) patients <65 years old had severe infection (ICU admission or death within 28 days of diagnosis), of whom 14 (28.0%) were IC. Proportionally, 16.7% of all RSV-associated deaths and 55.1% of all ICU RSV-admissions occurred in adult patients <65 years old. RSV accounted for 665 (10.1%) infections confirmed by 4-in-1 viral PCR testing. Eight-nine (13.4%), 172 (9.3%) and 448 (12.0%) patients with RSV, Influenza A and SARS-COV2 experienced severe infection, of whom 32 (36.0%), 82 (47.7%) and 156 (34.8%) were <65 years old respectively. Eight (25.0%), 20 (24.4%) and 52 (33.3%) of patients <65 years old with severe infection were IC. On adjusted analysis, having an immunosuppressive condition increased the odds of a severe SARS-CoV2 infection, OR (95% CI) 1.36 (1.08-1.71) but not a severe RSV or Influenza infection. ConclusionsSevere RSV infections occur in persons <65 years old, with a significant proportion of patients having an immunosuppressive condition. Urgent research is needed to investigate the potential benefit of extending the current UK RSV vaccine policy to protect younger immunosuppressed adults.

Background and objectives: Industrialisation is associated with lower gut microbial richness. The ecological insurance hypothesis proposes that richer communities buffer disturbance via overlapping functions, possibly affecting infection susceptibility. We state predictions, audit the evidence, and test the richness-infection relationship in Gambian children. Methodology: We analysed 452 children aged 6-35 months with Day 85 stool 16S profiles and dated infections over 113 days. Diversity used Hill numbers (q = 0, 1, 2); redundancy was inferred from reference-genome gene content. We examined associations with illness during follow-up and infections after Day 85, adjusting for earlier illness. Results: Richness was lower in children with any infection (93.9 vs 103.1; d = 0.36; adjusted odds ratio 0.989 per species, p = 0.019); abundance-weighted diversity was not. Most illness preceded sampling (295 of 315); the difference lay in common and intermediate-prevalence species. Richness was lowest around recent illness. Higher richness was associated with fewer later infections (rate ratio 0.69 per SD, 95% CI 0.51-0.93; q = 0.11). Redundancy correlated with richness at q = 0 (rho = 0.93); at q = 1-2 estimates indicated lower infection rates but none survived correction (smallest FDR q = 0.14). Conclusions and implications: Richness and infection were associated in both directions: children who had been ill had lower richness, and greater Day 85 diversity preceded fewer infections. Redundancy was directionally aligned with reduced infection at higher diversity orders, but FDR control and collinearity limit inference. Cohorts sampled before illness, with shotgun data, are needed.

Sepsis is a substantial contributor to neonatal mortality in Africa, with Klebsiella pneumoniae as the leading causative pathogen. Incorporating molecular tools such as whole genome sequencing (WGS) into routine surveillance of important bacterial pathogens, including those causing neonatal sepsis, can support targeted deployment of infection prevention and control measures and treatment interventions. This study aimed to understand the current practices and capacity for culture, identification and genomic analysis of bacterial pathogens in Africa, with a particular focus on K. pneumoniae, to support standardised genomic surveillance. A cross-sectional online survey was distributed to various clinician and scientist networks across Africa. All respondents completed a demographics section, while sections on laboratory test capacity, blood culture practices, WGS, and bioinformatics analysis were completed based on experience in these aspects. Responses were received from 52 institutions in 25 African countries. Among 51 institutions completing the laboratory test capacity section, 61% reported performing blood cultures, with the majority using manual commercial biochemical systems for species identification (71%) and manual disk diffusion for antibiotic susceptibility testing (82%). Participating institutions reported near-universal access to a -80{degrees}C freezer, centrifuge and thermocycler, but shaking incubators were less commonly available (67%). More than half of respondents (54%) indicated that they perform the entire WGS workflow (including DNA extraction, library preparation and WGS) internally, with most performing DNA extraction internally (88%) using column-based kits (70%). Outsourcing was progressively more common at later workflow stages. Infrastructure challenges that limit bioinformatics analysis capabilities were reported by all 23 respondents who completed this question, including limited access to high-performance computing and data storage space. This survey found sufficient capacity to support genomic surveillance of neonatal sepsis pathogens across participating African institutions. However, investments in blood culture, supply chains, sequencing, bioinformatics, and data dissemination capacity are needed to realise its full potential. These findings will support the development of standardised genomic surveillance protocols tailored to the diverse capacities of African laboratories.